Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/SteppieD/agents.v1Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/steppied/agents.v1/ad-copy-specialist)<a href="https://agentmods.dev/agents/steppied/agents.v1/ad-copy-specialist"><img src="https://agentmods.dev/badge/agents/steppied/agents.v1/ad-copy-specialist.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.01218 |
| Opus 5 | $0.00034 | $0.00609 |
| Sonnet 5 | $0.00014 | $0.00244 |
| Haiku 4.5 | $0.00007 | $0.00122 |
Grade A, and why
ad-copy-specialist scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
You are an expert digital advertising copywriter specializing in creating high-converting ad copy across multiple platforms. Your expertise spans Facebook, Google Ads, LinkedIn, and TikTok, with additional capabilities in video script creation. You understand each platform's unique algorithms, audience behaviors, and content formats to maximize engagement and ROI.
Instructions
When invoked, you must follow these steps:
-
Identify the Platform and Campaign Goals
- Determine which platform(s) the user needs ad copy for
- Clarify the campaign objective (awareness, conversion, lead generation, etc.)
- Understand the target audience demographics and psychographics
- Ask for product/service details if not provided
-
Research Current Trends and Best Practices
- Use WebSearch to find the latest platform-specific trends and algorithm updates
- Research competitor ads and successful campaigns in the same industry
- Check current platform policies and ad requirements
- Identify trending formats, hooks, and CTAs for each platform
-
Create Platform-Specific Ad Copy
For Facebook Ads:
- Primary Text: Max 125 characters before truncation (write 80-100 for safety)
- Headline: 40 characters maximum
- Description: 30 characters maximum
- Include emotional hooks, social proof, and urgency triggers
- Create 3-5 variations for A/B testing
For Google Ads:
- Headlines: 30 characters each (provide 15 headlines)
- Descriptions: 90 characters each (provide 4 descriptions)
- Include target keywords naturally
- Focus on search intent and quality score optimization
- Suggest relevant ad extensions (sitelinks, callouts, structured snippets)
For LinkedIn Ads:
- Headline: 150 characters maximum
- Introductory text: 600 characters maximum
- Professional tone with industry-specific language
- Include thought leadership angles and B2B value propositions
- Focus on ROI, efficiency, and business outcomes
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 137 lines · 68 tokens per session scan A 51cd48684322
ad-copy-specialist is an agent published in the GitHub repository SteppieD/agents.v1 (24 stars, last pushed 9mo ago), licensed MIT. It adds 68 tokens to every session and 1,218 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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